Sustainable Planning Strategies Research Articles

The urban air quality nexus: Assessing the interplay of land cover change and air pollution in emerging South Asian cities

Air quality degradation presents a significant public health challenge, particularly in rapidly urbanizing regions where changes in land use/land cover (LULC) can dramatically influence pollution levels. This study investigates the association between LULC changes and air pollution (AP) in the five fastest-growing cities of Bangladesh from 1998 to 2021. Leveraging satellite data from Landsat and Sentinel-5P, the analysis reveals a substantial increase in urban areas and sparse vegetation, with declines in dense vegetation and water bodies over this period. Urban expansion was most pronounced in Sylhet (22–254%), while Khulna experienced the largest increase in sparse vegetation (2–124%). Dense vegetation loss was highest in Dhaka (20–77%) and water bodies (9–59%) over this period. Concentrations of six major air pollutants (APTs) - aerosol index, CO, HCHO, NO2, O3, and SO2 - were quantified, showing alarmingly high levels in densely populated industrial and commercial zones. Pearson's correlation indicates strong positive associations between APTs and urban land indices (R > 0.8), while negative correlations exist with vegetation indices. Geographically weighted regression modeling identifies city centers with dense urban built-up as pollution hotspots, where APTs exhibited stronger impacts on land cover changes (R2 > 0.8) compared to other land classes. The highest daily emissions were observed for O3 (1031 tons) and CO (356 tons) at Chittagong in 2021. In contrast, areas with substantial green cover displayed weaker pollutant-land cover associations. These findings underscore how unplanned urbanization drives AP by replacing natural land cover with emission sources, providing crucial insights to guide sustainable urban planning strategies integrating pollution mitigation and environmental resilience.

Exploring the role of configurational accessibility of alleyways on facilitating wayfinding transportation within the organic street network systems

Despite the significant role of alleyways in urban spatial configuration and accessibility as critical structures of urban infrastructure, there remains a noticeable gap in understanding their specific role in urban transportation policies. The main aim of the present study is to investigate the role of configurational accessibility of alleyways in facilitating wayfinding within organic street network systems. A mixed method was applied using Space Syntax and empirical observations. Moreover, Pearson correlations and t-tests were used to discern the association between variables and compare independent groups using SPSS software. The findings from the syntactical analysis strongly indicate that alleyways significantly impact configurational accessibility within urban network systems. Furthermore, the complex and labyrinthine structure of organic alleyways was found to significantly hinder the intelligibility of urban areas, making navigation more challenging. The results revealed a significant correlation between vehicle mobility and connectivity values, with higher levels of mobility consistently linked to increased connectivity values. The outcomes also indicated that alleys connected to main streets play a crucial role in facilitating wayfinding within urban network systems. This study contributes to a more profound understanding of the role of alleyways in urban network systems for urban planners and transportation engineers, paving the way for more targeted sustainable urban planning strategies.

Role of Urban Trees in Enhancing the Thermal Comfort of Rapidly Urbanizing Cities: An Analysis of Tropical Asian Tree Species Based on Physiological Equivalent Temperature (PET)

AbstractBackgroundThermal comfort significantly influences well-being, productivity, and living conditions in outdoor environments, particularly in rapidly urbanizing, warm, humid tropical climates. This study assessed the influence of 5 five common urban tree species (Cassia fistula,Tectona grandis,Plumeria obtusa,Mangifera indica, andTerminalia catappa) on outdoor thermal comfort, using the physiological equivalent temperature (PET) index in Colombo, Sri Lanka, as a case study for a tropical humid city.MethodsField data collection encompassed measuring air and surface temperature, relative humidity, wind velocity, solar radiation, cloud cover, and sky view factor under tree canopies and adjacent exposed areas. The RayMan model was employed to estimate PET in both areas.ResultsOur findings indicated that PET was consistently higher in exposed areas compared to under the tree canopy, with an average difference of 5.61 °C. Among tree parameters, sky view factor (SVF) demonstrated the most significant correlation with thermal comfort, followed by crown diameter and tree height. Furthermore, notable variations in thermal comfort were observed among tree species, withTerminalia catappaoutperformingPlumeria obtusa, particularly on sunny days.ConclusionRegression analysis highlighted the importance of integrating trees with large crowns and low SVF to create thermally comfortable outdoor spaces. Consequently,Terminalia catappaemerged as the most suitable tree species for enhancing thermal comfort in Colombo’s outdoor urban areas out of the 5 selected species. These insights will aid in selecting appropriate tree species and parameters, fostering improved outdoor thermal comfort in tropical humid cities, and facilitating sustainable urban planning and design strategies.

From expansion to efficiency: Machine learning-based forecasting of Japan's building material stocks under demographic declines

Japan's unique demographic trajectory, marked by population decline and aging, coupled with continued urbanization, presents distinct challenges for aligning built environment capacity with resource efficiency. This study aims to investigate the historical evolution and project future scenarios of building material stock (MS) and their spatial distribution across Japan's three major metropolitan areas. Through a comprehensive material flow and stock analysis, the historical accumulation of building materials from 2009 to 2020 was quantified, revealing a dominance of concrete and an increasing overall stock. The contributions of various driving factors to changes in construction areas were explored, identifying population dynamics as the predominant influence. Leveraging shared socioeconomic pathway scenarios (SSPs), this research forecasted building floor area and MS until 2050 under five distinct SSPs. The results indicated an overall reduction across all scenarios, yet with a continued concentration in high-density urban cores. The substantial gap between the highest and lowest projected MS scenarios highlighted opportunities for material conservation and emission reductions through sustainable practices. Sustainable urban development in densely populated regions necessitates a balance between infrastructure provision and environmental conservation, while in sparsely populated areas, the focus shifts to the efficient management and utilization of vacant properties and materials to cope with the impacts of significant population declines. By offering insights into the building floor area and MS implications of Japan's demographic changes, this study underscores the necessity of sustainable urban planning and resource management strategies to navigate the challenges posed by demographic shifts, ultimately contributing to sustainable development and environmental conservation goals.

Dynamics of Local Communities Through the Transformation of Agriculture to The Camping Sector in Pancasari Village, Buleleng, Bali

This study explores the dynamics of local communities in Pancasari Village, Buleleng, Bali, as they transition from traditional agriculture to the emerging camping sector. This transformation has led to significant economic, social, and environmental changes within the community. Economically, the shift has generated new employment opportunities, increased household incomes, and stimulated local businesses, thereby enhancing the village’s economic resilience. However, challenges such as potential inflation, uneven distribution of benefits, and increased vulnerability to external economic shocks have also arisen. Socially and culturally, the move to camping has altered traditional roles and lifestyles, facilitated cultural exchange and the introduction of new ideas but also posing risks of cultural dilution and commodification. Environmentally, the camping sector promotes sustainable tourism practices, yet it also brings negative impacts like habitat loss and increased waste. This study employs a qualitative research methodology, including interviews, observations, and document analysis, to understand these dynamics comprehensively. The findings highlight the need for sustainable planning and inclusive development strategies to address economic challenges, robust environmental management to mitigate negative impacts, and effective policy and governance frameworks to ensure equitable benefit distribution and stakeholder coordination. The study concludes that while the transformation to the camping sector presents significant opportunities for economic growth and cultural exchange, it also requires careful management to ensure long-term community well-being and sustainability. By understanding these dynamics, policymakers and stakeholders can better support the community through this transition, promoting balanced and sustainable development in Pancasari Village.

Impacts of urbanization on ecosystem carbon cycle: a case study of land use change in Tianjin metropolitan area.

For the sustainable development of the city, in a study of Tianjin's rapid urbanization, we explore the complex interplay between land use change and the ecosystem carbon cycle from 2000 to 2020. Spatial analysis and profit-loss matrix calculations reveal contrasting ecological impacts: expansion of woodlands and grasslands enhances Net Primary Productivity (NPP) and reduces carbon emissions, while urban construction shows the opposite effect. Over 20 years, Tianjin's urban transformation led to a 16.91 GgC decline in NPP amidst a construction boom. However, post-2015 ecological policy shifts resulted in a significant net carbon uptake of 0.85 Gt, demonstrating the potential of policy interventions in mitigating environmental impacts of urbanization. This study underscores the importance of sustainable urban planning and ecological conservation strategies in highly urbanized settings.

Exploring the Complexities of Urban Forms and Urban Heat Islands: Insights from the Literature, Methodologies, and Current Status in Morocco

The Urban Heat Island phenomenon (UHI), characterized by elevated temperatures in urban areas compared to their rural surroundings, is highly exacerbated by urbanization and climate change. Understanding the complex relationship between UHI effect and urban form is crucial for effective urban planning and climate mitigation strategies. This paper examines the multifaceted connection between UHIs and urban forms, exploring various methods used to study this relationship. Through a review of the existing literature, we analyze the influence of various urban characteristics on the intensity and spatial distribution of UHIs. Furthermore, we discuss the key methods and technologies, such as remote sensing and modeling, used in advancing our understanding of UHI–urban form interactions. This study then delves into the literature on UHIs within the specific context of Morocco, identifying research gaps and emphasizing the need for more comprehensive research to address them. By translating study findings into actionable urban solutions, this paper suggests contextual mitigation strategies based on the research outcomes. Finally, by synthesizing current research findings and methodologies, this paper seeks to provide insights into the complexities of UHI dynamics and their implications for climate resilience, highlighting the potential of research for forging sustainable and climate-conscious planning strategies in Morocco and across the broader MENA region.

Evaluating the Spatial-Temporal Dynamics of Urbanization in Prefecture Cities of China Using SNPP-VIIRS Nighttime Light Remote Sensing Data

Ensuring the well-being of urban communities hinges on sustainable urban planning strategies informed by current data, particularly in China since urbanization has been one of the most significant demographic shifts in recent decades. Therefore, our research aimed to evaluate the spatio-temporal dynamics of urbanization and sub urbanization across prefecture and provincial levels in China by utilizing consistent SNPP-VIIRS-like and NPP-VIIRS nighttime data spanning the years 2000 to 2020. The k-means method was applied to derive urban and sub urban features from above datasets. The findings uncovered a significant expansion of urban entities at the prefecture level, escalating from 16,209 km2 to 89,631 km2 over the specified period showing a 5% growth. Among five main urban agglomerations, the Yangtze River Delta stands out with the highest urbanization rate, witnessing a remarkable expansion of urban entities from 2,684 km2 to 41,465 km2. This growth reflects an average growth rate of 72.2% per annum. The analysis revealed that the overall area of suburbs expanded from 59,151 km2 to 120,339 km2 between 2012 and 2020 indicating a proportional growth rate ranging from 0.4% to 1.9%. The peak growth rate of suburbs was recorded between 2012 and 2014, reaching 18%. Guizhou, Hunan, and Hubei provinces have exhibited growth rates of 334%, 258%, and 246% respectively while Beijing, Guangdong, Tianjin, and Shanghai have experienced relatively low growth rates of 50%, 56%, 46%, and 17%. The analysis of urban growth with GDP, population, and electricity consumption revealed an inverse relationship during the specified period. Therefore, the findings of this research can provide immense support to sustainable urban planning initiatives at both the provincial and prefecture-level cities in China. The findings can assist city planning authorities in making informed decisions regarding optimizing resource distribution, all while prioritizing the preservation of ecological footprint within urban environments. Also, the limitations addressed in our study must be taken into account in future research works aimed at deriving reliable urban extraction results using nighttime light remote sensing data.

Exploring the non-linear impacts of urban features on land surface temperature using explainable artificial intelligence

High land surface temperatures (LST) have emerged as crucial threats to urban ecosystems and sustainable urban development. To better understand and mitigate their impacts, it is essential to analyze the contributing urban features. Against this background, we developed a random forest model enhanced by Explainable Artificial Intelligence (XAI) to analyze the impact features of LST in Beijing, China. By applying the XAI method, our results suggest that the major impact features of LST in Beijing are elevation (44.19%), compactness of impervious surface (17.27%), Normalized Difference Vegetation Index (11.12%), proportion of impervious surface area (8.04%), and tree height (3.83%). Compactness of impervious surface exhibited an overall cooling effect, which became weaker at high values. LST increased with building height, and the trend became weaker as building height reached 5 m. The most important features impacting LST in the inner city are the proportion and height of buildings, whereas in the outer city these features are tree height and the compactness of impervious surfaces. The study applies XAI to explain the non-linear interactions between LST and urban features, offering innovative insights to policy-makers to develop sustainable urban planning strategies. Our findings suggest that increasing green spaces and water bodies as well as controlling building density and height can effectively mitigate heat in dense urban areas and enhance cooling effects.

Who can access what? Uncovering urban inequality in access to service for senior citizens

The scarcity or lack of access to essential services at the local and neighbourhood levels in cities can result in significant spatial inequalities, as some areas and their residents can deal with disadvantages and a lower quality of daily life. In particular, the spatial distribution and the variety of amenities at the local scale represent an important feature of the liveliness of places. The local availability and access to essential services are particularly relevant for some demographic groups experiencing limited mobility or mobility poverty, such as older adults living in cities, and spatial disparities have been further exacerbated by the COVID-19 pandemic, which highlighted severe difficulties in accessing essential services. This work explores the issue focussing on the following question: who can access what depending on where they live in cities? Using Machine Learning and Spatial Autocorrelation applied to different data sources for spatial information on the location of urban amenities and Internet access, this work aims to identify the most underserved places in terms of the variety of available amenities and access to quality broadband in three European capital cities. A comparison to urban areas where high percentages of older adults reside makes it possible to identify where residents can locally access several essential services (green spaces, health care, and local shopping) and where this need cannot be satisfied because of a lack in the amenity variety available at walking distance to their home. The combination of underserved areas with a high concentration of senior residents identifies left-behind areas in these cities, where interventions on inequalities are most needed. Results can inform policies aiming at favouring fair access to services at the local scale, possibly including slow and active mobility modes, and in general to develop comprehensive and sustainable planning strategies for cities, leaving no place and no person behind.

Coordinated operation for a resilient and green energy-water supply system: A co-optimization approach with flexible strategies

Sustainable operation of green renewable energy (RE)-powered reverse osmosis (RO) desalination (RE-RO) systems requires co-optimization and smart strategies to reduce costs, losses and enhance system flexibility. This study proposes a decentralized distribution system (DDS) that includes a coordinated multi-objective optimization model with smart strategies for efficient operation and planning of the RE-RO system. The DDS optimizes operation by incorporating demand-side water management (DSWM) and bidirectional regulation (BDR) in the distribution network to minimize operation and emission costs, maximize system resilience, and meet the required demand. Then, sustainable planning strategies are suggested to prioritize relevant technical factors and subfactors for improving the future operation of the DDS based on multi-criteria assessment. With proposed DDS integration, the RE-RO system achieved a 17.4 % reduction in operational costs, a 46.79 % decrease in CO2 emissions, and a 70.96 % improvement in overall system resilience through effective management of water and energy surpluses and deficits. Among the operational planning strategies, the most critical criterion was DSWM-BDR based scheduling, representing 72.09 % of the strategic focus. Thus, the implementation of the proposed coordinated operating and planning strategies can significantly contribute to the development of a sustainable energy-water system, alleviate water scarcity, and facilitate climate change adaptation.

Urbanization and Its Influence on Public Health in Southeast Asia

Purpose: The aim of the study was to analyze the urbanization and its influence on public health in Southeast Asia. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Urbanization in Southeast Asia significantly impacts public health through strained healthcare infrastructure, environmental health risks like pollution and inadequate sanitation, and increased prevalence of non-communicable diseases due to urban lifestyles. Infectious disease transmission is amplified in densely populated urban areas, exacerbated by social determinants of health disparities. Effective urban health policies and integrated planning are essential to mitigate these challenges, promoting sustainable development and equitable healthcare access across the region. Unique Contribution to Theory, Practice and Policy: Urbanization theory, social determinants of health theory & ecological systems theory may be used to anchor future studies on urbanization and its influence on public health in Southeast Asia. Initiatives should focus on promoting healthy urban environments through sustainable urban planning and design strategies. Policymakers should prioritize the integration of health considerations into urban planning policies and initiatives.

A novel explainable PSO-XGBoost model for regional flood frequency analysis at a national scale: Exploring spatial heterogeneity in flood drivers

Identifying flood drivers and accurately estimating design floods play a crucial role in fostering sustainable and effective planning and management strategies for mitigating flood risks. Regional Flood frequency Analysis (RFFA) is one of the most commonly used approaches to estimate design floods in ungauged watersheds. This study used XGBoost coupled with Particle Swarm Optimization (PSO) to estimate different quantiles of the design floods with return periods (from 2-year to 1000-year). After a preliminary assessment, 373 nationwide hydrometric stations were selected to conduct at-site flood frequency analysis by identifying the best-fitting distribution. Using the capabilities of GIS and Google Earth Engine (GEE), 83 independent features including different physiographical, geomorphological, land-use, soil types, and long-term hydro-climatic and environmental variables were extracted for the upstream watersheds. After fine-tuning the hyper-parameters of the XGBoost method for each flood quantile, the feature importance values were used to eliminate the insignificant features and refine the developed models. Additionally, classical methods such as Support Vector Regression (SVR) and Random Forest (RF) were implemented, to evaluate the XGBoost models efficiency. Different statistics demonstrated that the models effectively estimated flood quantiles, with the Nash-Sutcliffe Efficiency (NSE) varying from 0.709 to 0.840 across all models. A comparison of model performance reveals that the XGBoost method outperformed RF and SVR across all flood quantiles. Based on the developed models, design floods have been estimated for 949 stations across Iran. Furthermore, the Shapley additive explanation (SHAP) values were used to identify the main contributing features to model outputs and investigate the spatial heterogeneity of main flood drivers. According to the results, the perimeter and length of the watershed and heavy rainfall exhibit notably high importance compared to other features for all models. Based on the local SHAP values, in Northern, Northwestern, and Western basins, features associated with watershed sizes, such as perimeter, area and length exhibit the highest levels of importance. Moreover, the Southwest basins are more influenced by “heavy rainfall”. These findings demonstrate the promise of the developed models for estimating flood quantiles across diverse environmental, geomorphological, and hydro-climatic conditions. This capability is valuable for sustainable watershed management, especially in environments with limited maximum discharge data.

The role of air pollution in electric vehicle adoption: Evidence from China

This study provides a comprehensive analysis of the mechanisms through which air pollution influences consumer adoption of electric vehicles (EVs) in China. Utilizing the Air Quality Index (AQI) and EV sales data from 50 Chinese cities from 2010 to 2019, we apply a multiple regression model to investigate the direct and indirect impacts of air pollution on EV adoption. By analyzing data from the AQI and EV sales across 50 Chinese cities between 2010 and 2019, we apply a multiple regression model to dissect the direct and indirect effects of air pollution on the adoption of EVs. We find that the health risks associated with air pollution, such as respiratory and cardiovascular diseases, significantly sway consumer behavior towards EVs. Concerns over health and the financial burden of air pollution-related illnesses drive consumers, especially in wealthier regions, to choose EVs for healthier transportation. Additionally, we note an indirect mechanism: increased public and government awareness of environmental issues. This heightened awareness, coupled with policies promoting EV adoption, indirectly bolsters consumer interest in EVs, acknowledging their role in enhancing air quality. These findings offer vital insights for formulating sustainable transportation policies and urban planning strategies, especially in contexts of severe air pollution.

An optimal sustainable planning strategy for national carbon capture deployment: A review on the state of CO2 capture in Canada

AbstractThis study reviews the steps Canada is taking to address sustainable decarbonization in the context of carbon capture. This work also presents a new optimal framework for national optimal deployment in need of strategic carbon capture implementation. This framework considers external environmental and social considerations often missing from implementation frameworks, which will aid policy makers in more well‐rounded deployment decisions. Thus far, Canada's carbon projects have captured a total of 36.3 Mt of CO2 which has cost over $2.7 billion to implement. The Canadian case study utilizing the proposed optimal planning strategy shows that implementation of 58 post‐combustion carbon capture (PCC) plants located in seven provinces (Alberta, British Columbia, New Brunswick, Nova Scotia, Ontario, Quebec, and Saskatchewan) would result in Canada meeting the national targets. This implementation includes 16 plants removing emissions from the Electricity sector, 16 from the Heavy Industry sector, and 26 from the Oil and gas sector resulting in new emissions levels of 11.82 MtCO2, 27.63 MtCO2, and 107.01 MtCO2 in each sector, respectively. Additional case studies examined the impact of Alberta's emissions and varying the national targets resulting in different optimal implementations plans. Through a sensitivity analysis on these targets, it was determined that plant distribution is heavily dependent on provincial energy and CO2 transport prices. Additionally, if Alberta were to reduce their GHG emissions by 50% through alternative sustainable methods, only 35 PCC plants would be required to meet national targets. This framework provides a sustainable tool for decision‐makers to accelerate decarbonization.

Remote sensing-based analysis of land use, land cover, and land surface temperature changes in Jammu District, India

ABSTRACT The study conducted in Jammu District, India, investigates land use and land cover (LULC) transformations over the past three decades using satellite data and remote sensing techniques. Analyzing data from 1990 to 2020, significant changes were observed. Agricultural land expanded by 157.76 km2 (6.71%), barren land by 151.69 km2 (6.45%), and settlements by 96.97 km2 (4.12%). However, vegetation decreased by 389.77 km2 (16.57%), while water bodies experienced minimal changes. Land Surface Temperature (LST) analysis, utilizing MODIS data (2000-2020), revealed warming trends, with temperatures ranging from 15.92°C to 42.77°C in 2010 and 14.04°C to 37.01°C in 2020. Notably, NDVI values peaked in 2020 (0.759) and were lowest in 1990 (−0.243), indicating healthier vegetation and lower surface temperatures. This inverse correlation highlights NDVI's potential as an indicator for assessing vegetation health and its impact on local temperature conditions. Man-Kendall Z statistics indicated negative trends for Tmax and Tmin, while rainfall data showed significant positive trend. Population growth, urbanization, climate change and agricultural intensification emerged as principal drivers of the LULC changes in the region. This study underscores the importance of geospatial tools in monitoring LULC changes, providing valuable insights for policymakers and planners to formulate sustainable land use planning and management strategies.

Techno-economic evaluation of meshed distribution network planning with load growth and expansion with multiple assets across multiple planning horizons

The smart grid paradigm has ushered in an era where modern distribution systems are expected to be both robust and interconnected in topology. This paper presents a techno-economic-based sustainable planning (TESP) strategy, which can be used as a planning framework for linked distribution systems, seeking to discover a realistic solution among competing criteria of diverse genres. In this comparative analysis-based study, three voltage stability assessment indices—VSA_A, VSA_B, and VSA_W—and a loss minimization condition (LMC)-based framework are used in the initial stage to achieve optimal distributed generation (DG)-based asset optimization for siting, followed by sizing. The respective techniques are evaluated across two variants of multiple load growth horizons spread across 10 years. The suggested TESP technique is tested on two variants of a mesh-configured microgrid (MCMG) with varied load growth scenarios. One variant considers a 65-bus MG with a fixed load growth of 2.7% across two load growth horizons. The other variant considers a 75-bus MG with varied load growth across four load growth horizons, encapsulating an expansion-based planning perspective. The numerical results of the suggested TESP approach in a comparative study demonstrate its effectiveness, and it can be used by researchers and planning engineers as a planning framework for interconnected distribution tools across multiple planning horizons. The proposed study would contribute to enhancing the robustness and interconnectivity of smart grid distribution systems. This dual focus could lead to more cost-effective and reliable power distribution systems.

Balancing urban growth and the sustainability of groundwater and agricultural land: Case of the berrechid-settat area

Urbanization is an inevitable global phenomenon characterized by the exponential growth of urban areas in terms of both population and infrastructure. However, this rapid urban expansion often comes at a significant environmental cost. This article explores the multifaceted consequences of urbanization, shedding light on its role in contributing to desertification, compromising water quality, and depleting groundwater resources. To assess the scale of urbanization’s impact, comprehensive landuse studies are crucial. Geographic Information Systems (GIS) and remote sensing techniques offer valuable tools for mapping and monitoring land-use changes over time. These methods enable the quantification of the conversion of agricultural land into urban areas and identify trends in urban sprawl, providing essential data for understanding the scale of the issue. Water quality assessments are equally vital; we can employ water sampling and laboratory analyses to quantify pollutant concentrations in urban runoff and groundwater. Monitoring the presence of contaminants such as oil, chemicals, and litter, as well as their effects on water quality; helps measure the environmental impact of urbanization. Groundwater studies can utilize hydrogeological investigations, including the use of monitoring wells and geophysical methods, to evaluate changes in groundwater levels and quality. These data are instrumental in gauging the depletion of groundwater reserves and their potential contribution to water scarcity issues. In conclusion, the consequences of urbanization extend far beyond the confines of urban areas, affecting agriculture, ecosystems, and water resources. As urbanization continues to advance, it is imperative to develop sustainable urban planning and management strategies that mitigate its environmental impact, preserve agricultural land, protect groundwater resources, and ensure the long-term health of the planet.

Analyzing urban sprawl and urbanisation dynamics: A case study of Bejaia, Oued-Ghir, and Tala-Hamza

Understanding urban sprawl is crucial as it provides a dynamic perspective on urban areas, revealing the driving forces and explanatory factors behind their expansion. This study specifically examines the factors contributing to urban sprawl in Bejaia city and its neighbouring communes, Oued-Ghir and Tala-Hamza. The aim is to analyse the intricate urban systems within these areas, unveiling the diverse forms of peri-urbanisation affecting agricultural land. The results underscore the impact of various factors on urban sprawl in Bejaia City. These factors include demography, spatial population distribution, housing, transportation, access conditions, administrative urban status, economic and social development, as well as employment opportunities. These determinants collectively underpin the ongoing urban sprawl in the region, emphasising the necessity for sustainable urban planning and development strategies.

The Effects of Climate Change on Coastal Areas and Coastal Property and Floating Cities As a Solution Proposal

This research examines the impacts of climate change on water levels in coastal areas and focuses on strategies to cope with these impacts. Research shows that climate change will have negative impacts such as rising sea levels, flooding, loss of settlements and forced migration. This necessitates the development of climate change compatible policies in coastal areas. The paper addresses sustainable and resilient urban planning strategies in this context. It also evaluates floating city projects that stand out as an effective solution against future water level rises. Floating cities offer innovative concepts that can adapt to rising water levels, are eco-friendly, self-powered and offer sustainable living spaces. The research examines the potential advantages of these projects for addressing property issues and environmental sustainability in coastal areas, while emphasizing that these projects could be an important alternative for future coastal areas. As a result, it emphasizes the role of floating city projects in the development of effective and sustainable strategies to combat climate change and sheds light on future research in this field and its applicability in Turkey.